Evidence map›Paper›PMID 39748855›Full record

ArticleIEEE access : practical innovations, open solutions2024

Spatial Deep Learning Approach to Older Driver Classification.

Charles Boateng, Seyedeh Gol Ara Ghoreishi, Kwangsoo Yang, Muhammad Tanveer Jan, Ruth Tappen, Jinwoo Jang, David Newman, Sonia Moshfeghi, Kelly Jackson, Rhian Resnick and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Charles BoatengFlorida Atlantic University, Boca Raton, USA.
Seyedeh Gol Ara GhoreishiFlorida Atlantic University, Boca Raton, USA.
Kwangsoo YangFlorida Atlantic University, Boca Raton, USA.
Muhammad Tanveer JanFlorida Atlantic University, Boca Raton, USA.
Ruth TappenFlorida Atlantic University, Boca Raton, USA.
Jinwoo JangFlorida Atlantic University, Boca Raton, USA.
David NewmanFlorida Atlantic University, Boca Raton, USA.
Sonia MoshfeghiFlorida Atlantic University, Boca Raton, USA.
Kelly JacksonFlorida Atlantic University, Boca Raton, USA.
Rhian ResnickFlorida Atlantic University, Boca Raton, USA.
Borko FurhtFlorida Atlantic University, Boca Raton, USA.
Monica RosselliFlorida Atlantic University, Boca Raton, USA.
Joshua ConniffFlorida Atlantic University, Boca Raton, USA.

Funding

In-Vehicle Sensors to Detect Cognitive Change in Older DriversR01AG068472 · NIA · FLORIDA ATLANTIC UNIVERSITY · PI NEWMAN, DAVID, TAPPEN, RUTH M · 2020 to 2024
$5.5M
NIA NIH HHS R01 AG068472
6 · The paper itself

Abstract

Given telemetry datasets (e.g., GPS location, speed, direction, distance.), the Older Driver Classification (ODC) problem identifies two groups of drivers: normal and abnormal. The ODC problem is essential in many societal applications, including road safety, insurance risk assessment, and targeted interventions for elderly drivers with dementia or Mild Cognitive Impairment (MCI). The problem is challenging because of the volume and heterogeneity of temporally-detailed vehicle datasets. This paper proposes a novel spatial deep-learning approach that leverages Grid-Index based data augmentation to enhance the detection of abnormal driving behaviors. Through extensive experiments and a real-world case study, the proposed approach consistently identifies abnormal drivers with high accuracy. The findings demonstrate the potential of grid-based methods to improve telematics-based driving behavior analysis significantly. This approach offers valuable implications for enhancing road safety measures, optimizing insurance risk assessments, and developing targeted interventions for at-risk drivers.

Indexed as

Older Driver ClassificationSpatial Deep LearningTrajectory Data Mining

Identifiers

PMID39748855
PMCPMC11694628

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.